Control charts are one of the main tools that quality managers in manufacturing use to conduct and present statistical analysis. To date, they have not been very popular with contact center quality managers. Is there a place for control charts in the contact center?
The control chart was originally used to present how a particular statistic varied over time. This is a very important measurement for production managers in the automotive and other engineering industries where machines produce parts that must fit together with a high level of precision. The chart shows the stability of a series of measurements carried out over a period of time. The more stable the measurement is, the more predictable the process is.
It goes without saying that contact center agents are not machines. Call quality cannot be measured anywhere near as precisely as tolerances in a machine part produced by a computer controlled lathe, so how can control charts be of any use to a contact center manager?
Would you believe this team managers' sales forecasts?
The control chart above shows the daily results of a contact center’s sales team for a month. The blue line represents the actual sales results for each day of calling, while the green represents the average, and the yellow and red represent 1 or 2 standard deviations above and below the average. The width of the band represented on the chart by the standard deviation lines is a pretty good reflection of how stable the sales process is and therefore how reliable the sales managers’ promises are to head office.
A quality manager might be very interested in the result where sales went more than 2 standard deviations above the average. They might reflect a rare moment of inspiration in the sales team, or they might reflect a new and convincing lie that a sales agent has started telling the customer. Needless to say, the days where the sales results fall below the average will also need to be investigated.
Is this quality process working?
Quality management and feedback is also a process which can be shown on a control chart. The illustration above shows a control chart for a contact center providing customer support. The blue line represents the actual quality scores over the month, the black line represents the overall trend, the green line represents the average, while the yellow and red lines represent 1 and 2 standard deviations below the average respectively.
What is very noticeable is how far 1 and 2 standard deviations are from the average. This shows that the quality process is not particularly stable. If each data point represents a quality evaluation, it is not hard to see which evaluations are pulling the score down and to investigate what happened and find out what corrective measures can be taken to follow up.
These charts can also be used for educational purposes to show agents and operations team leads the effect poor results have on the team’s overall performance. The visual impact of the chart is likely to be more meaningful than a dry recital of figures and will enable everyone in the contact center to see, understand and act on the “big picture” better.
